The Collingridge dilemma is a methodological quandary in which efforts to influence or control the further development of technology face a double-bind problem:
The idea was coined by David Collingridge at the University of Aston Technology Policy Unit in his 1980 book The Social Control of Technology. [1] The dilemma is a basic point of reference in technology assessment debates. [2]
In "This Explains Everything," edited by John Brockman, technology critic Evgeny Morozov explains Collingridge's idea by quoting Collingridge himself: "When change is easy, the need for it cannot be foreseen; when the need for change is apparent, change has become expensive, difficult, and time-consuming." [3]
In "The Pacing Problem, the Collingridge Dilemma & Technological Determinism" by Adam Thierer, a senior research fellow at the Mercatus Center at George Mason University, the Collingridge dilemma is related to the "pacing problem" in technology regulation. The "pacing problem" refers to the notion that technological innovation is increasingly outpacing the ability of laws and regulations to keep up, first explained in Larry Downes' 2009 book The Laws of Disruption , in which he states that "technology changes exponentially, but social, economic, and legal systems change incrementally". In Thierer's essay, he tries to correlate these two concepts by saying that "the 'Collingridge dilemma' is simply a restatement of the pacing problem but with greater stress on the social drivers behind the pacing problem and an implicit solution to 'the problem' in the form of preemptive control of new technologies while they are still young and more manageable." [4]
One solution to Collingridge dilemma is the "Precautionary Principle." Adam Thierer defines it as the belief that new innovations should not be embraced "until their developers can prove that they will not cause any harm to individuals, groups, specific entities, cultural norms, or various existing laws, norms, or traditions". [4] If they fail to do so, this innovation should be "prohibited, curtailed, modified, junked, or ignored". [5] This definition has been criticized by Kevin Kelly who believe such a principle is ill-defined [4] and is biased against anything new because it drastically elevates the threshold for anything innovative. According to the American philosopher Max More, the Precautionary Principle "is very good for one thing — stopping technological progress...not because it leads in bad directions, but because it leads in no direction at all." [5] But the 1992 Rio Declaration on Environment and Development defines the precautionary principle as ""Where there are threats of serious or irreversible damage, lack of full scientific certainty shall not be used as a reason for postponing cost-effective measures to prevent environmental degradation." [6] So rather than conceived as imposing no change until proof of safety is produced, this definition of the precautionary principle is meant to legitimate protective measures, attempting to avoid the desire of a technology's advocates to delay legislation until irrefutable evidence of harm can be produced.
Collingridge's solution was not exactly the precautionary principle but rather the application of "Intelligent Trial and Error," a process by which decision making power remains decentralized, changes are manageable, technologies and infrastructures are designed to be flexible, and the overall process is oriented towards learning quickly while keeping the potential costs as low as possible. [7] Collingridge advocated ensuring that innovation occurs more incrementally so as to better match the pace of human learning and avoiding technologies whose design was antithetical to an Intelligent Trial and Error process.
The Collingridge Dilemma applies well to a world where Artificial Intelligence and Cloud are gaining ground and developers are consuming new technology at a rapid pace. Governing AI, Cloud or other similar exponential technology without slowing the pace of development of the technology is a big challenge, governments and organizations now face.
In business theory, disruptive innovation is innovation that creates a new market and value network or enters at the bottom of an existing market and eventually displaces established market-leading firms, products, and alliances. The term, "disruptive innovation" was popularized by the American academic Clayton Christensen and his collaborators beginning in 1995, but the concept had been previously described in Richard N. Foster's book "Innovation: The Attacker's Advantage" and in the paper Strategic Responses to Technological Threats.
The precautionary principle is a broad epistemological, philosophical and legal approach to innovations with potential for causing harm when extensive scientific knowledge on the matter is lacking. It emphasizes caution, pausing and review before leaping into new innovations that may prove disastrous. Critics argue that it is vague, self-cancelling, unscientific and an obstacle to progress.
Technology assessment is a practical process of determining the value of a new or emerging technology in and of itself or against existing technologies. This is a means of assessing and rating the new technology from the time when it was first developed to the time when it is potentially accepted by the public and authorities for further use. In essence, TA could be defined as "a form of policy research that examines short- and long term consequences of the application of technology."
Innovation is the practical implementation of ideas that result in the introduction of new goods or services or improvement in offering goods or services. ISO TC 279 in the standard ISO 56000:2020 defines innovation as "a new or changed entity, realizing or redistributing value". Others have different definitions; a common element in the definitions is a focus on newness, improvement, and spread of ideas or technologies.
Technology governance means the governance, i.e., the steering between the different sectors—state, business, and NGOs—of the development of technology. It is the idea of governance within technology and its use, as well as the practices behind them. The concept is based on the notion of innovation and of techno-economic paradigm shifts according to the theories by scholars such as Joseph A. Schumpeter, Christopher Freeman, and Carlota Perez.
In futures studies and the history of technology, accelerating change is the observed exponential nature of the rate of technological change in recent history, which may suggest faster and more profound change in the future and may or may not be accompanied by equally profound social and cultural change.
Social construction of technology (SCOT) is a theory within the field of science and technology studies. Advocates of SCOT—that is, social constructivists—argue that technology does not determine human action, but that rather, human action shapes technology. They also argue that the ways a technology is used cannot be understood without understanding how that technology is embedded in its social context. SCOT is a response to technological determinism and is sometimes known as technological constructivism.
Theories of technological change and innovation attempt to explain the factors that shape technological innovation as well as the impact of technology on society and culture. Some of the most contemporary theories of technological change reject two of the previous views: the linear model of technological innovation and other, the technological determinism. To challenge the linear model, some of today's theories of technological change and innovation point to the history of technology, where they find evidence that technological innovation often gives rise to new scientific fields, and emphasizes the important role that social networks and cultural values play in creating and shaping technological artifacts. To challenge the so-called "technological determinism", today's theories of technological change emphasize the scope of the need of technical choice, which they find to be greater than most laypeople can realize; as scientists in philosophy of science, and further science and technology often like to say about this "It could have been different." For this reason, theorists who take these positions often argue that a greater public involvement in technological decision-making is desired.
The difference between material culture and non-material culture is known as culturallag. The term cultural lag refers to the notion that culture takes time to catch up with technological innovations, and the resulting social problems that are caused by this lag. In other words, cultural lag occurs whenever there is an unequal rate of change between different parts of culture causing a gap between material and non-material culture. Subsequently, cultural lag does not only apply to this idea only, but also relates to theory and explanation. It helps by identifying and explaining social problems to predict future problems in society. The term was first coined in William F. Ogburn's 1922 work Social Change with Respect to Culture and Original Nature.
There are several approaches to defining the substance and scope of technology policy.
A technological fix, technical fix, technological shortcut or (techno-)solutionism refers to attempts to use engineering or technology to solve a problem.
A smart city is a technologically modern urban area that uses different types of electronic methods and sensors to collect specific data. Information gained from that data is used to manage assets, resources and services efficiently; in return, that data is used to improve operations across the city. This includes data collected from citizens, devices, buildings and assets that is processed and analyzed to monitor and manage traffic and transportation systems, power plants, utilities, urban forestry, water supply networks, waste, criminal investigations, information systems, schools, libraries, hospitals, and other community services. Smart cities are defined as smart both in the ways in which their governments harness technology as well as in how they monitor, analyze, plan, and govern the city. In smart cities, the sharing of data is not limited to the city itself but also includes businesses, citizens and other third parties that can benefit from various uses of that data. Sharing data from different systems and sectors creates opportunities for increased understanding and economic benefits.
Technology dynamics is broad and relatively new scientific field that has been developed in the framework of the postwar science and technology studies field. It studies the process of technological change. Under the field of Technology Dynamics the process of technological change is explained by taking into account influences from "internal factors" as well as from "external factors". Internal factors relate technological change to unsolved technical problems and the established modes of solving technological problems and external factors relate it to various (changing) characteristics of the social environment, in which a particular technology is embedded.
The technological innovation system is a concept developed within the scientific field of innovation studies which serves to explain the nature and rate of technological change. A Technological Innovation System can be defined as ‘a dynamic network of agents interacting in a specific economic/industrial area under a particular institutional infrastructure and involved in the generation, diffusion, and utilization of technology’.
A reverse salient refers to a component of a technological system that, due to its insufficient development, prevents the system in its entirety from achieving its development goals. The term was coined by Thomas P. Hughes, in his work Networks of power: Electrification in western society, 1880-1930.
Transition management is a governance approach that aims to facilitate and accelerate sustainability transitions through a participatory process of visioning, learning and experimenting. In its application, transition management seeks to bring together multiple viewpoints and multiple approaches in a 'transition arena'. Participants are invited to structure their shared problems with the current system and develop shared visions and goals which are then tested for practicality through the use of experimentation, learning and reflexivity. The model is often discussed in reference to sustainable development and the possible use of the model as a method for change.
Demand articulation is a concept developed within the scientific field of innovation studies which serves to explain learning processes about needs for new and emerging technologies. Emerging technologies are technologies in their early phase of development, which have not resulted in concrete products yet. Many characteristics of these technologies, such as the technological aspects but also the needs of users concerning the technology, have not been specified yet. Demand articulation can be defined as ‘iterative, inherently creative processes in which stakeholders try to address what they perceive as important characteristics of and attempt to unravel preferences for an emerging innovation’.
Technological transitions (TT) can best be described as a collection of theories regarding how technological innovations occur, the driving forces behind them, and how they are incorporated into society. TT draws on a number of fields, including history of science, technology studies, and evolutionary economics. Alongside the technological advancement, TT considers wider societal changes such as "user practices, regulation, industrial networks, infrastructure, and symbolic meaning or culture". Hughes refers to the 'seamless web' where physical artifacts, organizations, scientific communities, and social practices combine. A technological transition occurs when there is a major shift in these socio-technical configurations.
Technological determinism is a reductionist theory that assumes that a society's technology progresses by following its own internal logic of efficiency, while determining the development of the social structure and cultural values. The term is believed to have originated from Thorstein Veblen (1857–1929), an American sociologist and economist. The most radical technological determinist in the United States in the 20th century was most likely Clarence Ayres who was a follower of Thorstein Veblen and John Dewey. William Ogburn was also known for his radical technological determinism and his theory on cultural lag.
Mutual shaping suggests that society and technology are not mutually exclusive to one another and, instead, influence and shape each other. This process is a combination of social determinism and technological determinism. The term mutual shaping was developed through science and technology studies (STS) in an attempt to explain the detailed process of technological design. Mutual shaping is argued to have a more comprehensive understanding of the development of new media because it considers technological and social change as directly affecting the other.